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Vatsalpatni73/README.md

Hey there 👋, I'm Vatsal Patni

Third Year Undergrad · IIT (BHU) Varanasi · Civil Engineering
Systems programmer, open-source contributor & competitive coder


🧑‍💻 About Me

I'm a systems-focused developer who loves working deep in the stack — Kubernetes internals, concurrent C++, and distributed resource management. Currently contributing to CNCF projects while honing DSA and competitive programming skills.

  • 🎓  B.Tech in Civil Engineering at IIT (BHU) Varanasi (CGPA: 7.97, Class of 2027)
  • 🌐  Active CNCF / Kubernetes open-source contributor (Koordinator project)
  • 🏆  JEE Advanced qualifier — top 1% of engineering aspirants nationwide
  • ⚔️  Meta Hacker Cup 2025 — progressed to Round 2, ranked 1,570th globally

🔧 Tech Stack

Domain Technologies
Languages C / C++, Go, Python, JavaScript, SQL
Core Areas DSA, OOP, Kubernetes Internals, Distributed Systems, Multithreading & Concurrency, Memory & Cache Management
Frameworks & Platforms React.js, Vite, Tailwind CSS, Recharts, Koordinator, Kubernetes Admission Webhook Framework, Prometheus
Developer Tools Git, GitHub, kubectl, Vercel, Jupyter Notebook, Codecov

🚀 Open Source Contributions

Koordinator — CNCF Kubernetes QoS-based Resource Management  May 2026

Go · Kubernetes Internals · koordlet · Admission Webhooks · slo-controller

Resource Management

  • Fixed BE resource helpers (GetPodBEMilliCPU*, GetPodBEMemoryByte*) to correctly account for init containers and pod.Spec.Overhead per Kubernetes semantics — #2918 (milestone v1.8.1)
  • Registered MidCPU / MidMemory into ExtendedResourceNames#2940

koordlet & Prediction

  • Added --default-qos-class-for-guaranteed-pods flag with parse-time validation — #2926
  • Introduced computePodSampleWeight for priority-aware and cold-start-ramped histogram weighting in predict_server#2980

Webhook & Device Plugin

  • Refactored pod mutating handler into shared runMutatingPlugins for UPDATE support — #2958
  • Replaced binary StatusRejected with structured error codes in webhook metrics — #2944
  • Added runtime GPU/NPU resource registration to gpudeviceresource plugin — #2953

QuantLib — Industry-Standard Quantitative Finance C++ Library  Merged

C++ · Numerical Methods · Hull-White Model · Compiler Optimization

  • Diagnosed and fixed a test failure in testCachedHullWhite triggered specifically under g++ 12.x with -O3 optimization — a subtle floating-point precision issue that only surfaced at high compiler optimization levels — #2435
  • Adjusted numerical tolerance in test-suite/shortratemodels.cpp from 1.2e-51.3e-5 to correctly accommodate valid floating-point variance introduced by aggressive compiler optimizations, without relaxing test integrity

🛠️ Projects

C++ · Memory Management · File I/O · Huffman Coding

A high-performance lossless file compressor leveraging Huffman coding and multi-core concurrency.

  • Implemented lossless Huffman compression with mutexes and condition variables for thread synchronization
  • Benchmarked on a 500 MB dataset — achieved a 63% reduction in execution latency (25.1s → 9.3s) by scaling from single-threaded to 4-worker concurrent execution

Codeforces Profile Visualizer  ·  Live Link  ·  GitHub

React.js · Vite · Tailwind CSS · Recharts · Codeforces API · Vercel

A responsive single-page analytics dashboard to visualize and compare Codeforces user profiles side-by-side.

  • Built a full-featured SPA with React + Vite + Tailwind CSS rendering contest history, rating trends, and problem tag distribution with interactive Recharts components — submission heatmaps, rating history graphs, and tag distribution charts for granular performance analysis
  • Engineered a robust data-fetching layer against the Codeforces REST API; implemented sessionStorage caching (capped at 2,000 entries) and graceful retry logic to handle HTTP 429 rate-limiting and minimize network overhead

Pathfinding Visualizer

C++ · SFML · STL (Vector, Queue, Priority Queue)

A real-time graph traversal engine with visual rendering of pathfinding algorithms.

  • Engineered runtime execution of Dijkstra & Bidirectional A* optimized for low-latency visual output
  • Flattened 2D grid allocations into contiguous 1D arrays — reduced heap fragmentation and maximized L1/L2 CPU cache locality
  • Implemented Bidirectional A* with Manhattan distance heuristics, cutting the search space from O(b^d) → O(b^(d/2))

🏅 Achievements

🥇 JEE Advanced — Top 1% of engineering aspirants nationwide
🌍 Meta Hacker Cup 2025 — Qualified & progressed to Round 2 · 1,570th globally
Codeforces — Specialist · Rating 1518 · Handle: LASTAV
💡 LeetCode — Knight · Rating 1878 · Handle: vatsalpatni
📜 STSE — Secured Rank 365 in the State Talent Search Examination

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